Interpolating with -lambda 1.0

[Tanel Alumäe]

Hello,

I'm a bit confused with interpolation.
I want to calculate test text's perplexity using different interpolation
weights (lambdas). Everything is OK until I set lambda to 1.0. Shouldn't
I then get the same perplexity as using only the base language model?
This doesn't seem to be the case:

$ ngram -lm trigram.arpa -ppl <testtxt> 
file <testtxt>: 2394 sentences, 29475 words, 1224 OOVs
0 zeroprobs, logprob= -86274.9 ppl= 653.583 ppl1= 1132.06

$ ngram -lm trigram.arpa -ppl <testtxt> -classes <classdefs>  -mix-lm
class-trigram.arpa -lambda 1.0
file <testtxt>: 2394 sentences, 29475 words, 1224 OOVs
0 zeroprobs, logprob= -85554.4 ppl= 619.144 ppl1= 1067.5

As shown, the perplexity is 653.539 when using standalone trigram, and
619.144 when interpolating the trigram with the class-trigam, using
lambda 1.0. Why are they not equal?

Both word trigram and class trigram are close-vocabulary LMs, if it
matters.

Regards,

Tanel A.